Test¶

import pandas as pd
import seaborn as sns
import plotly.express as px
from itables import init_notebook_mode
init_notebook_mode(all_interactive=True)

cities = pd.read_json('https://www.visimarsrutai.lt/services-ext/api/municipalities')

cities

id	name
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from urllib.request import urlopen
import json
with urlopen('https://raw.githubusercontent.com/plotly/datasets/master/geojson-counties-fips.json') as response:
    counties = json.load(response)

import pandas as pd
df = pd.read_csv("https://raw.githubusercontent.com/plotly/datasets/master/fips-unemp-16.csv",
                 dtype={"fips": str})

import plotly.express as px

fig = px.choropleth_mapbox(df, geojson=counties, locations='fips', color='unemp',
                           color_continuous_scale="Viridis",
                           range_color=(0, 12),
                           mapbox_style="carto-positron",
                           zoom=3, center = {"lat": 37.0902, "lon": -95.7129},
                           opacity=0.5,
                           labels={'unemp':'unemployment rate'}
                           )
fig.update_layout(margin={"r":0,"t":0,"l":0,"b":0})
fig.show()

import plotly.express as px

df = px.data.election()
geojson = px.data.election_geojson()

fig = px.choropleth_mapbox(df, geojson=geojson, color="winner",
                           locations="district", featureidkey="properties.district",
                           center={"lat": 45.5517, "lon": -73.7073},
                           mapbox_style="carto-positron", zoom=9)
fig.update_layout(margin={"r":0,"t":0,"l":0,"b":0})
fig.show()

import pandas as pd
import plotly.express as px

#import dataset
df = pd.read_csv('https://covid.ourworldindata.org/data/owid-covid-data.csv')

#select entries with the continent as asia
df = df[df['date'] == '2021-02-04']
df = df[df.continent == 'Asia']

display(df)
with urlopen('https://raw.githubusercontent.com/plotly/datasets/master/geojson-counties-fips.json') as response:
    counties = json.load(response)

#plot
fig = px.choropleth(df, geojson=counties, locations="iso_code",
                    color="new_cases",
                    hover_name="location",
                           featureidkey="properties.district",
                    title = "Daily new COVID cases",
                     color_continuous_scale=px.colors.sequential.PuRd,
                        )

fig["layout"].pop("updatemenus")
fig.show()

WARNING:itables.downsample:showing 49x20 of 49x67 as maxColumns=20. See https://mwouts.github.io/itables/downsampling.html

	iso_code	continent	location	date	total_cases	new_cases	new_cases_smoothed	total_deaths	new_deaths	new_deaths_smoothed	female_smokers	male_smokers	handwashing_facilities	hospital_beds_per_thousand	life_expectancy	human_development_index	excess_mortality_cumulative_absolute	excess_mortality_cumulative	excess_mortality	excess_mortality_cumulative_per_million
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MaaS plėtra

Test

Test¶